Visual Analysis for Spatio-Temporal Event Correlation in Manufacturing

dc.contributor.author Herr, Dominik
dc.contributor.author Kurzhals, Kuno
dc.contributor.author Ertl, Thomas
dc.date.accessioned 2020-01-04T07:25:17Z
dc.date.available 2020-01-04T07:25:17Z
dc.date.issued 2020-01-07
dc.description.abstract The analysis of events with spatio-temporal context and their interdependencies is a crucial task in the manufacturing domain. In general, understanding this context, for example investigating error messages or alerts is important to take corrective actions. In the manufacturing domain, comprehending the relations of errors is often based on the technicians' experience. Validation of cause-effect relations is necessary to understand if an effect has a preceding causality, e.g., if an error is the result of multiple issues from previous working steps. We present an approach to investigate spatio-temporal relations between such events. Based on a time-sensitive correlation measure, we provide multiple coordinated views to analyze and filter the data. In collaboration with an industry partner, we developed a visual analytics approach for error logs reported by machines that covers a multitude of analysis tasks. We present a case study based on real-world event logs of an assembly line with feedback from our industry partner's domain experts. The findings show that experts can effectively identify error dependencies that impair the overall assembly line productivity using our technique. Furthermore, we discuss how our approach is applicable in other domains.
dc.format.extent 10 pages
dc.identifier.doi 10.24251/HICSS.2020.164
dc.identifier.isbn 978-0-9981331-3-3
dc.identifier.uri http://hdl.handle.net/10125/63903
dc.language.iso eng
dc.relation.ispartof Proceedings of the 53rd Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Interactive Visual Analytics and Visualization for Decision Making – Making Sense of a Growing Digital World
dc.subject event analysis
dc.subject manufacturing
dc.subject spatio-temporal data
dc.subject visual analytics
dc.subject visualization
dc.title Visual Analysis for Spatio-Temporal Event Correlation in Manufacturing
dc.type Conference Paper
dc.type.dcmi Text
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